class_docstr: EfficientNet stage.
code: def __init__(self, w_in, exp_r, k, stride, se_r, w_out, d):
      super(EffStage, self).__init__()
      for i in range(d):
          block = MBConv(w_in, exp_r, k, stride, se_r, w_out)
          self.add_module("b{}".format(i + 1), block)
          stride, w_in = 1, w_out
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, drop_connect, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, SE
  from torch.nn import Dropout, Module
label_desc: Use image node_id 1 to create a new EffStage object from inherited base classes: Module with example: obj = EffStage(w_in, exp_r, k, stride, se_r, w_out, d)